Name : Dr. K. VIJAYAKUMAR
Designation : Associate Professor
Qualification : MCA, Ph.D. (UoH)
Email-id : email@example.com
Experience : 20 Years
Teaching experience : 20 Years
Research Interests : Data mining, Machine Learning and related areas
VIJAYA KUMAR KADAPPA obtained his Ph.D. in computer science from central University of Hyderabad in 2010 and working as Associate Professor at Department of Computer Applications, BMS College of Engineering, Bangalore, since April 2012. Prior to joining BMSCE, he worked as Associate professor about 5 years and as Asst. professor about 7 yrs. in Vasavi College of Engineering Hyderabad. His research interests are in Data Mining and Machine Learning. He received his Bachelor degree in Science from Sri Krishna Devaraya University, Anantapur, AP, India in 1995 and Master degree in Computer Applications from University of Mysore, India in 1998. He has 20 years of teaching and research experience. He executed a R&D project funded by UGC during 2014-2016. He is currently supervising 3 Ph.D. scholars in the area of Machine learning. Dr. Kadappa has 24 publications and published his research papers in several International journals (5 Elsevier science/ 2 Springer journals) and IEEE/Springer conferences. Dr. Kadappa is a life member of Indian Unit of International Association of Pattern Recognition, ISTE and Computer Society of India.
- Ph.D. (Computer Science), School of CIS, University of Hyderabad (Central University), Telangana.
- Supervisor: Dr. Atul Negi
- Title of thesis: Feature partitioning approaches to Principal Component Analysis
- M.C.A., Dept.of Studies in CS, Manansagangothri, University of Mysore, Karnataka.
- B.Sc.(Maths, Physics, Statistics), Govt. Degree College, Anantapur, AP.
Selected Publications (International Journals :7)
- Vijayakumar Kadappa and Shivaraju Nagesh, `Local support based Partition algorithm for fre-quent pattern maining', Pattern Analysis and Applications (Springer International Journal), Accepted in Sept. 2018 [Impact factor (2017): 1.28].
- Vijayakumar Kadappa, Shankru Guggari and Umadevi V, `Non-Sequential Partitioning Approaches to Decision Tree classi_er', Future Computing and Informatics Journal (Elsevier Science Publishers), Accepted in Aug. 2018 [Scopus Indexed].
- Vijayakumar Kadappa and Atul Negi, `A Theoretical Investigation of Feature Partitioning Principal Component Analysis Methods', Pattern Analysis and Applications (Springer International Journal), Vol. 19, Issue 1, pp: 79-91, Feb. 2016 [Impact factor (2017): 1.28].
- Vijayakumar Kadappa and Atul Negi, `Global Modular Principal Component Analysis', Signal Processing (Elsevier Science International Journal), Vol. 105, pp: 381-388, Dec. 2014 [Impact
Factor (2017): 3.47].
- Vijayakumar Kadappa and Atul Negi, `Computational and Space Complexity Analysis of SubXPCA', Pattern Recognition (Elsevier Science International Journal), Vol. 46, Issue 8, pp: 2169-2174, Aug. 2013 [Impact factor (2017): 3.962].
- Vijayakumar Kadappa and Atul Negi, `SubXPCA and a Generalized Feature Partitioning Approach to Principal Component Analysis', Pattern Recognition (Elsevier Science International Journal), Vol. 41, Issue 4, pp: 1398-1409, Apr. 2008 [Impact factor (2017): 3.962].
- Vijayakumar Kadappa and Atul Negi, `Novel Approaches to Principal Component Analysis of Image Data based on Feature Partitioning Framework', Pattern Recognition Letters (Elsevier Science International Journal), Vol. 29, Issue 3, pp: 254-264, Feb. 2008 [Impact factor (2017): 1.952].
Publications in International Conferences: 17
IEEE: 10 Springer: 3 World Scientific: 1 Others: 3
Courses Handled/List :
- Machine Learning
- Data mining
- Software Project Management
- Discrete mathematics
- Computer organization
- Software Engineering
- User interface design
- An R&D project on Teacher recruitment modeling funded by UGC was executed during 2014-16.
- Research paper incentive awarded by BMSCE in 2013, 2014, and 2016
- Reviewer for many international conferences
- Curriculum development for courses:
Statistics, Data science, Machine Learning, Big data analytics, Software Project Management, Discrete mathematics, Deep Learning.
- Invited talks:
- Research talk on Feature partitioning based PCA methods in Researchers enclave on Computational Intelligence and Machine Learning held at Aditya Institute of Technology, Coimbatore from 7th to 8th Sept. 2012.
- Resource person for TEQUIP II sponsored 1 week FDP on Machine Learning (Two sessions on PCA and Teacher Recruitment Case studies) by JNTU College of Engineering, Kukatpally, Hyderabad on 15th April 2016.
- Resource person at One week FDP on “Mathematical modeling for Research problems” organized by Dept. of MCA, BMSITM during 25th to 29th June 2018. Topic: Mathematical modeling in Data mining (26th June 2018)